Evaluation of Synthetic Small-area Estimators Using Design-based Methods

Abstract

The use of area-specific design-based mean squared error (MSE) to measure the uncertainty associated with synthetic and direct estimators is appealing since the same model-free criterion is applied. However, the small sample size is often a difficulty in obtaining a reliable estimator of the area-specific design-based MSE. Moreover, the area-specific design-based mean squared error estimator might yield undesirable negative values under certain circumstances. The existing solution to overcome the problem of small sample size is to consider average design-based MSE, average being taken over the available small areas. This may not solve the other problem of negative MSE. An alternative average design-based mean squared error estimator is proposed which always produces positive estimates. Simulation shows that this estimator performs better than the existing average design-based MSEs as it always produces positive estimates and accounts for the bias component usually present in synthetic estimators.